CAEP/ACMU 2014 Scientific Abstracts, May 31 to June 4, 2014, Ottawa, Ontario
Bibliographic record
Abstract
Research in emergency medicine addresses issues that affect all aspects of patient care, including clinical decision rules, wait times, overcrowding, improved practice guidelines based on best evidence, and new applications for diagnostic tools.Fostering a rich research environment requires education, funding, and a rigorous peer-review process.The Research Committee is pleased to have continued its support of these efforts.Research-based abstracts are the core of the annual research competition, and this year, there was a record number of submissions for the CAEP 2014 Conference in Ottawa.We received abstracts from emergency medicine researchers from across Canada and internationally.The top ranking abstracts submitted by CAEP members were afforded the opportunity to present at the plenary session, and the best resident, pediatric, and medical student abstracts were awarded financially to subsidize conference travel expenses.The promotion and dissemination of high-quality research, like that submitted to the CAEP 2014 Conference, is integral to the enhancement of Canadian emergency medicine research.Accompanying these customary research-based education abstracts, the Research Committee accepted education innovation abstracts.These abstracts highlight the novel ideas, methods, and materials developed by emergency medicine educators and focus on curricula, teaching methods, and assessment.The Research Committee has incorporated these innovation abstracts throughout the sessions, as lightning orals, moderated posters, and posters.As part of the Research Committee commitment to support emergency medicine researchers, five CAEP research grants were awarded for the best proposals submitted by medical students, residents, and junior investigators.These small grants are known to have successfully launched new projects and the careers of new emergency medicine researchers by providing funds at a pivotal point.The funding of these grants requires the support of generous members of our community, so remember to support the Research Committee.Although not sufficiently recognized, the work of the volunteer reviewers is critically important to the success of the Research Committee activities during the abstract and grant competitions.Each submission is thoroughly read, reviewed, and scored by at least three experienced reviewers.Those submitting grant proposals are supplied with detailed reviewer comments, providing valuable feedback for these junior investigators.The Research Committee would like to thank the reviewers for their hours of work and recognize their commitment to support emergency medicine research.Finally, CAEP is dedicated to supporting Canadian emergency medicine research and is looking forward to continuing these efforts to encourage new and established researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.568 | 0.198 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".